def get(self,param):
"""
Get a value from sqlite database.
There can be only one experiment id per loader. Returns an array
containing time-dependent data or a single value. User does not
need to worry which table the data is stored in, i.e whether it
is of the sim_var, output_data etc.. types.
"""
try:
self.data=sqldbutils.sim_data(self.db_path,self.experiment_id,param) #try and get the time-correlated samples for that param
var=self.data.samples #first try and load time-varying data if it exists
if len(var)>0:
variable=var
except:
pass
connection=sqldbutils.db_connect(self.db_path)
#try and get it from output_params table using SQL query:
try:
query='SELECT numerical_value FROM output_params WHERE parameter=\''+param+'\' AND experiment_id ='+str(self.experiment_id)
numerical_value=sqldbutils.execute_query(connection,query).fetchall()[0][0]
if type(numerical_value)!=None:
variable=numerical_value
except:
pass
try:
query='SELECT string_value FROM output_params WHERE parameter=\''+param+'\' AND experiment_id ='+str(self.experiment_id)
string_value=sqldbutils.execute_query(connection,query).fetchall()[0][0]
if type(string_value)!=None:
variable=string_value
except:
pass
#try and get it from sim_var table using SQL query:
try:
query='SELECT numerical_value FROM sim_var WHERE parameter=\''+param+'\' AND experiment_id ='+str(self.experiment_id)
numerical_value=sqldbutils.execute_query(connection,query).fetchall()[0][0]
if type(numerical_value)!=None:
variable=numerical_value
except:
pass
try:
query='SELECT string_value FROM sim_var WHERE parameter=\''+param+'\' AND experiment_id ='+str(self.experiment_id)
string_value=sqldbutils.execute_query(connection,query).fetchall()[0][0]
if type(string_value)!=None:
variable=string_value
except:
pass
try:
return variable #will either return a single value or time-varying (array)
except:
print 'Parameter not found in database'
def __local_evaluate(self, candidates, args):
import time
analysis
self.CandidateData_list = []
analysis_var = self.analysis_var
#Build submitfile.submit and runx.sh files:
self.__buil_condor_files(
candidates
) #exp_id now corresponds to position in chromosome/fitness array
fitness = []
#submit the jobs to the grid
os.chdir(self.tmpdir)
os.system('condor_submit submitfile.submit')
#wait till you know file exists:
dbs_created = False
while (dbs_created == False):
print('checking if dbs created:')
for job_num in range(self.num_jobs):
jobdbname = 'outputdb' + str(job_num) + '.sqlite'
jobdbpath = os.path.join(self.datadir, jobdbname)
print(jobdbpath)
db_exists = os.path.exists(jobdbpath)
if (db_exists == False):
time.sleep(60)
dbs_created = False
break
dbs_created = True
for CandidateData in self.CandidateData_list:
job_num = CandidateData.job_num
dbname = '/outputdb' + str(job_num) + '.sqlite'
dbpath = self.datadir + dbname
exp_id = CandidateData.exp_id
exp_data = sqldbutils.sim_data(dbpath, exp_id)
analysis = analysis.IClampAnalysis(exp_data.samples, exp_data.t,
analysis_var, 5000, 10000)
exp_fitness = analysis.evaluate_fitness(
self.targets,
self.weights,
cost_function=analysis.normalised_cost_function)
fitness.append(exp_fitness)
for job_num in range(self.num_jobs):
jobdbname = 'outputdb' + str(job_num) + '.sqlite'
jobdbpath = os.path.join(self.datadir, jobdbname)
print(jobdbpath)
os.remove(jobdbpath)
return fitness
def get_timeseries(self,param):
"""
Get a time vector corresponding to a value
Returns an array containing time-vector of a related value, typically
this will be a voltage recording.
"""
try: #first try and get
data=sqldbutils.sim_data(self.db_path,experiment_id=self.experiment_id,param=param)
return data.t
except:
print 'no such data'
def __local_evaluate(self,candidates,args):
import time
analysis
self.CandidateData_list=[]
analysis_var=self.analysis_var
#Build submitfile.submit and runx.sh files:
self.__buil_condor_files(candidates) #exp_id now corresponds to position in chromosome/fitness array
fitness=[]
#submit the jobs to the grid
os.chdir(self.tmpdir)
os.system('condor_submit submitfile.submit')
#wait till you know file exists:
dbs_created=False
while (dbs_created==False):
print('checking if dbs created:')
for job_num in range(self.num_jobs):
jobdbname='outputdb'+str(job_num)+'.sqlite'
jobdbpath=os.path.join(self.datadir,jobdbname)
print(jobdbpath)
db_exists=os.path.exists(jobdbpath)
if (db_exists==False):
time.sleep(60)
dbs_created=False
break
dbs_created=True
for CandidateData in self.CandidateData_list:
job_num = CandidateData.job_num
dbname='/outputdb'+str(job_num)+'.sqlite'
dbpath=self.datadir+dbname
exp_id=CandidateData.exp_id
exp_data=sqldbutils.sim_data(dbpath,exp_id)
analysis=analysis.IClampAnalysis(exp_data.samples,exp_data.t,analysis_var,5000,10000)
exp_fitness=analysis.evaluate_fitness(self.targets,self.weights,cost_function=analysis.normalised_cost_function)
fitness.append(exp_fitness)
for job_num in range(self.num_jobs):
jobdbname='outputdb'+str(job_num)+'.sqlite'
jobdbpath=os.path.join(self.datadir,jobdbname)
print(jobdbpath)
os.remove(jobdbpath)
return fitness
def run(self,candidates,parameters):
import sqldbutils
exp_data_array=[]
for chromosome in candidates:
self.chromosome=chromosome
self.parameters=parameters
exp_id = sqldbutils.generate_exp_ids(self.db_path)
cla=self.__generate_cla()
os.chdir(self.nrnproject_path+'/src/') #there should be a smarter way
os.system(cla)
print self.db_path
print exp_id
exp_data=sqldbutils.sim_data(self.db_path,exp_id)
exp_data_array.append(exp_data)
return exp_data_array
def run(self, candidates, parameters):
#"""Run simulations"""
import sqldbutils
exp_data_array = []
for chromosome in candidates:
self.chromosome = chromosome
self.parameters = parameters
exp_id = sqldbutils.generate_exp_ids(self.db_path)
cla = self.__generate_cla()
os.chdir(self.nrnproject_path +
'/src/') #there should be a smarter way
os.system(cla)
print(self.db_path)
print(exp_id)
exp_data = sqldbutils.sim_data(self.db_path, exp_id)
exp_data_array.append(exp_data)
return exp_data_array
'sqlite',experiment_id=1)
print loader.get('simulation_name')
#example of getting an item which was result of a calculation,
#saved using writer.write method of writer object at runtime
print loader.get('example value')
#loading the voltage-vector of a recording:
soma_voltage_2=loader.get('soma_voltage_2_mV')
#get the corresponding time-vector
t=loader.get_timeseries('soma_voltage_2_mV')
###PART 2 - using sqldbutils.py###
import sqldbutils
#note:REPLACE FILEPATH
db_path='/home/mike/dev/nrnproject/sims/outputdb.sqlite'
#create an exp_data object for that experiment
exp_data=sqldbutils.sim_data('/home/mike/dev/nrnproject/sims/output.sqlite',1)
#collect raw data, currently only loads voltage_mV timeseries
t= exp_data.t
samples=exp_data.samples
#examples of how to extract other qyery-dependent data (sqlite database)
connection=sqldbutils.db_connect('/home/mike/dev/nrnproject/sims/output.sqlite')
query_output=sqldbutils.execute_query(connection,'SELECT experiment_id FROM output_params WHERE parameter=\'example_param_2\' AND numerical_value>1')
exp_ids=query_output.fetchall()
